Causal Inference
Assessment of unmeasured confounding in the association between perceived discrimination and mental health in a predominantly African American cohort using g-estimation Jiajun Luo* Jiajun Luo Briseis Aschebrook-Kilfoy Loren Saulsberry
Background: Perceived discrimination in healthcare settings can have adverse consequences on mental health in minority groups. However, the association between perceived discrimination and mental health is prone to confounding because of difficulty to measure. The study aims to quantitatively evaluate the influence of unmeasured confounding in this association using g-estimation.
Methods: In a predominantly African American cohort, we applied g-estimation to estimate the association between perceived discrimination and mental health, adjusted and unadjusted for measured confounders. Mental health was measured using clinical diagnoses of anxiety, depression, and bipolar disorder. Perceived discrimination was measured as the number of patient-reported discrimination events in healthcare settings. Measured confounders included demographic, socioeconomic, residential, and health characteristics. The influence of confounding was denoted as α1 from g-estimation. Particularly, the α1 for measured confounding was denoted as α1*. We compared α1 for measured and unmeasured confounding.
Results: Strong associations between perceived discrimination in healthcare settings and mental health were observed. For anxiety, per one more patient-reported discrimination events, the OR (95% CI) unadjusted and adjusted for measured confounders were 1.30 (1.21, 1.39) and 1.26 (1.17, 1.36), respectively. The α1* for measured confounding was –0.066. Unmeasured confounding with α1=0.200, which was over three times that of measured confounding, corresponds to a relative rate of 1.12 (1.01, 1.24). Similar results were observed for other outcomes.
Conclusion: Compared to measured confounding, unmeasured confounding that was over three times was not enough to explain away the association between perceived discrimination and mental health, suggesting that this association is robust to unmeasured confounding. This study provides a novel framework to quantitatively evaluate unmeasured confounding.
